If you're using it to serve the marketing team, then yeah. We use it more for server performance and metrics that cookie-cutter JS analytics tools can't really provide.

btw, JS-based analytics are no longer as accurate for identifying "real humans" as they used to be. bots have gotten much better at behaving like a person behind a keyboard, so it's increasingly easy for them to make your analytics tool think they're a real user

This is not untrue, but I suppose that if you don't prevent bots from accessing your website, they won't try to use the more advanced scrapers running JS and won't trigger your analytics.

It's a oneliner for us, we run Caddy at the office and just specify --log-format=CADDY --keep-last=90 --date-spec=min and a single instance is ingesting ~100M/req a month

and honestly, there's still no other tool that does what GoAccess does quite as well. Most of the alternatives are cookie-cutter, JS-based Google Analytics wannabes. And with bots becoming much smarter and more prevalent when accessing websites, relying solely on JS-based tracking isn't as trustworthy anymore. We use GoAccess to capture what JS-based analytics can't, e.g., server side perf and traffic data. It's not meant to serve the marketing team though.

We use it on our site, which handles around 100M requests per month, works really nice. In fact, we have a screen in the office that continuously displays the stats, quite nifty!

I believe JS analytics tools serve marketing well, providing estimates like who's purchasing my product or how many are reading my article.

However, for devops, relying too much on these tools can be a trap, potentially causing security and server issues without immediate detection. Our team opts for goaccess for this reason. We prioritize accurate data from logs and scrutinize traffic patterns, focusing beyond just distinguishing between human and bot counts, a task we leave to the marketing/product department.

I think many developers overlook this aspect. If you're not in marketing, it's not just about tallying human visitors on our sites. It's essential to be vigilant against possible daily attacks and avoid excessive reliance on basic JS analytics.

Even for personal websites, relying solely on JS can compromise security. We require precise data, and logs prove more dependable than JS, especially with the increasing number of tools tampering with JS data.

We should steer clear of the trap of exclusively focusing on the count of human visitors.

JS analytics are increasingly susceptible to inaccuracies as data manipulation methods multiply, leading to the production of unreliable events from JavaScript endpoints. Staying abreast of industry developments highlights a rising trend of blockers leveraging AI-driven detection, reducing the significance of JavaScript analytics in such situations.

While JS analytics may suit the needs of marketing professionals concerned with product sales and article visibility, those focused on precise traffic patterns, like daily devops, find GoAccess to be a more effective tool.

JS analytics face an escalating risk of inaccuracies due to the myriad ways data can be manipulated, resulting in the generation of unreliable events from JavaScript endpoints. Keeping up with the industry reveals an emerging trend of blockers using AI-driven detection, diminishing the relevance of JavaScript analytics in such scenarios.

I would contend the contrary. Our company consistently runs GoAccess because we are primarily concerned with unusual traffic patterns. This involves monitoring for potential attacks or abnormal bot traffic that might impact our servers, etc.

While JS analytics tools might be of more interest to the marketing team, they are not as crucial for the devops team.

If accuracy refers solely to human-vs-bot detection, there might be a point, but for comprehensive traffic analysis, access logs are unparalleled in accuracy.

JavaScript analytics are increasingly prone to inaccuracies due to numerous methods available for manipulating data, leading to the generation of inaccurate events from JavaScript endpoints. Staying current in the field reveals a growing trend of blockers employing AI-driven detection, rendering JavaScript analytics less relevant in these cases.